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Uncertainty analysis of terrestrial net primary productivity and net biome productivity in China during 1901-2005
Shao J.; Zhou, X. H.; Luo, Y. Q.; Zhang, G. D.; Yan, W.; Li, J. X.; Li, B.; Dan, L.; Fisher, J. B.; Gao, Z. Q.; He, Y.; Huntzinger, D.; Jain, A. K.; Mao, J. F.; Meng, J. H.; Michalak, A. M.; Parazoo, N. C.; Peng, C. H.; Poulter, B.; Schwalm, C. R.; Shi, X. Y.; Sun, R.; Tao, F. L.; Tian, H. Q.; Wei, Y. X.; Zeng, N.; Zhu, Q.; Zhu, W. Q.
Source PublicationJournal of Geophysical Research-Biogeosciences
2016
Volume121
Issue5
Pages1372-1393
KeywordChina interannual variability model structure net primary productivity net biome productivity uncertainty model intercomparison project program multiscale synthesis carbon-dioxide interannual variability ecosystem exchange land-use nitrogen deposition global change soil respiration biosphere models
AbstractDespite the importance of net primary productivity (NPP) and net biome productivity (NBP), estimates of NPP and NBP for China are highly uncertain. To investigate the main sources of uncertainty, we synthesized model estimates of NPP and NBP for China from published literature and the Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP). The literature-based results showed that total NPP and NBP in China were 3.351.25 and 0.140.094PgCyr(-1), respectively. Classification and regression tree analysis based on literature data showed that model type was the primary source of the uncertainty, explaining 36% and 64% of the variance in NPP and NBP, respectively. Spatiotemporal scales, land cover conditions, inclusion of the N cycle, and effects of N addition also contributed to the overall uncertainty. Results based on the MsTMIP data suggested that model structures were overwhelmingly important (>90%) for the overall uncertainty compared to simulations with different combinations of time-varying global change factors. The interannual pattern of NPP was similar among diverse studies and increased by 0.012PgCyr(-1) during 1981-2000. In addition, high uncertainty in China's NPP occurred in areas with high productivity, whereas NBP showed the opposite pattern. Our results suggest that to significantly reduce uncertainty in estimated NPP and NBP, model structures should be substantially tested on the basis of empirical results. To this end, coordinated distributed experiments with multiple global change factors might be a practical approach that can validate specific structures of different models.
Indexed BySCI
Language英语
ISSN2169-8953
DOI10.1002/2015jg003062
Citation statistics
Document TypeSCI/SSCI论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/43187
Collection历年回溯文献
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GB/T 7714
Shao J.,Zhou, X. H.,Luo, Y. Q.,et al. Uncertainty analysis of terrestrial net primary productivity and net biome productivity in China during 1901-2005. 2016.
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